Introduction to Python related modules

1. Python references extension modules

• import <module>[as <alias>]: Import functions and other names in the module into the current program, "namespace" namespace, reference method——<module>.<name>

• dir (<name>) function: lists the attributes of the name

• help(<name>) function: display the reference manual

• from <module>import <name>: part of the name of the imported module

2. Time related modules

calendar module

• Several functions and classes related to calendar can generate calendar in text form

• calendar.calendar(<year>)

• calendar.month(<year>,<month>), returns a multi-line string

• calendar.isleap(<year>), to distinguish leap years

• calendar.prmonth(<year>,<month>)

• calendar.prcal(<year>)

datetime module

• There are 4 main categories: date processing year, month and day, time processing hour, minute, second, millisecond, datetime processing date plus time, timedelta processing period (time interval)

• Common functions/methods: datetime.date.today(), datetime.datetime.now(), datetime.datetime.isoformat()

• Subtracting two times is timedelta

time module

• The current time represented by time.time() floating point numbers: the number of seconds since 1970-1-1 0:0:0

•Time.struct_time structured time class: time.localtime(<epoch time>)->structure, time.gmtime(<epoch time>)->structure, time.mktime(<structured time>)->epoch time

• time.strftime(<format>) represents formatted output (structured) time

• time.strptime(<string>,<format>) identifies the string according to the format and returns the time

3. Arithmetic Module

• math: commonly used arithmetic functions, trigonometric functions, power exponents, etc.

• cmath: math function that supports complex numbers

• Decimal: Decimal fixed point, decimal decimal, there is no longer floating point error

• fractions: rational numbers, proportions, fractional calculations

• random: random number.

random.randint(a,b)，random.randrange(start,stop,step) ，

random.choice(seq)，random.sample(seq,n)。

• statistics: some statistical functions.

Average: mean, median: median, standard deviation: stdev/pstdev.

Fourth, persistence: shelve

• Save any data object to a file

• Similar to dictionary access, readable and writable: import shelve, f = shelve.open(<file name>), f[key] = value, value = f[key], del f[key], f.close( ).